Patient assistance system in a super speciality hospital using a Kinect sensor camera

Jyothilakshmi, P; Rekha, K R; Nataraj, K. R.

doi:10.1109/iceeot.2016.7754775

Cited by 2 publications

(1 citation statement)

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“…Furthermore, they also utilized the fusion of oximeter sensors and cameras for monitoring the health of COVID-19 patients. Apart from this, Jyothilakshmi et al [4] utilized a Kinect camera to recognize the gesture of the patients. They utilized trained ML classifiers to enable smart wards and health monitoring systems.…”

Section: Related Work a Health Monitoring Systemsmentioning

confidence: 99%

i-Sheet: A Low-Cost Bedsheet Sensor for Remote Diagnosis of Isolated Individuals

2023

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In this article, we propose a smart bedsheeti-Sheet-for remotely monitoring the health of COVID-19 patients. Typically, real-time health monitoring is very crucial for COVID-19 patients to prevent their health from deteriorating. Conventional healthcare monitoring systems are manual and require patient input to start monitoring health. However, it is difficult for the patients to give input in critical conditions as well as at night. For instance, if the oxygen saturation level decreases during sleep, then it is difficult to monitor. Furthermore, there is a need for a system that monitors post-COVID effects as various vitals get affected, and there are chances of their failure even after the recovery. i-Sheet exploits these features and provides the health monitoring of COVID-19 patients based on their pressure on the bedsheet. It works in three phases: 1) sensing the pressure exerted by the patient on the bedsheet; 2) categorizing the data into groups (comfortable and uncomfortable) based on the fluctuations in the data; and 3) alerting the caregiver about the condition of the patient. Experimental results demonstrate the effectiveness of i-Sheet in monitoring the health of the patient. i-Sheet effectively categorizes the condition of the patient with an accuracy of 99.3% and utilizes 17.5 W of the power. Furthermore, the delay involved in monitoring the health of patients using i-Sheet is 2 s which is very diminutive and is acceptable.

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Section: Related Work a Health Monitoring Systemsmentioning

confidence: 99%